Genómica Funcional en Investigación Biomédica

Pedro Jares Pathology Department, Hospital Clinic, Barcelona

Genomics Unit, IDIBAPS

Functional Genomics-Personalized Medicine

modif ied from Francis S. Collins, et.al.Nature 422, 835-847(24 April 2003)

GENOMICS TOOLS GENOMICS TOOLS

DNA sequence (mutations) DNA variation (SNPs, CNVs)

Structural genomics Histone modifications

DNA methylation

Gene expression

Splicing variants

DNA microarrays

(2) Transcriptome

(3) Proteome

(3) Metabolome

Profile and function

of metabolites

Protein expression

Post-translational modi- fications Structural and functional

analysis

mRNA and

non-coding RNA

Ge

no

mic

s

Tra

ns

cri

pto

mic

s

Pro

teo

mic

s

Me

tab

olo

mic

s

FUNCTIONAL GENOMICS

(1) Genome

DNA sequence

Structural genomics Epigenetics

Microarray: Universal Biochemistry Platform

Small molecules Carbohydrates

peptides proteins

DNA

A microarray is a compact device that contains a large number of well-defined

immobilized capture molecules assembled in an addressable format.

Synthetic oligos, PCR products, proteins, antibodies, carbohydrates etc….

a) You can expose an unknown

(test) sample on it and then examine

where the molecule was captured.

b) You can then derive information on

identity and amount of captured molecule.

Array Life Cycle amplifying coating

analyzing

scanning hybridizing

labelling

processing

printing

Biological

Question

from D. Petersen ATC/NCI

?

Types of Array

cDNA Oligonucleotides

Robotic Printing

Long oligos

(50-80 nt)

Short oligos

(<30 nt)

Synthesis in situ

Ink Jet

Technology (60nt, Agilent)

Maskless (60-70 nt

Nimblegen)

Photolithography (25 nt, Affymetrix)

Long oligos (50nt)

address seq (29 nt)

Bead-random

Arrays (Illumina)

Detection Two-color

Cy3

Cy5 Biotin

SAPE (Streptavidin

Phycoerythrin)

Cy3

Cy5

SA_Cy3 (Streptavidin

Cyanine 3)

Biotin

One-color

1) Probe Array

1.28cm

PM

MM

2) Probe set

Each Probe Set contains

11 Probe Pairs (PM:MM)

of different probes

cDNA sequence 5

3

GeneChip® and Probe selection

11-20 Oligonucleotides/ gene

Probe set

Probe selectiom

Up to ~1,400,000

features / chip 11µm

* * * * * * 4) Probe cell

Each Probe Cell contains

5x105-6 copies of a specific

probe 11µm

3) Probe pair

Each Perfect Match

(PM) and Mismatch

(MM) Probe Cells are

Associated by pairs

ATTAACGGGCATTGCATTAGCACGT

ATTAACGGGCTTAGCATTAGCACGT

Perfect match oligo (PM)

Mismatch oligo (MM)

BeadArrays: assembly of a random array

Kevin L. Gunderson et al. Genome Res. 2004; 14: 870-877

3µm pool

n-thousands bead types

Randomly array

beads into wells

adress

29bp

probe

50bp

Bead identifier Gene-specific

probe

3µm

Bead

Decode each bead using

hybridisation to address sequence

DMAP Files

The BeadChip decode

map files (.dmap)

48000 probe

average 30x

99.99 % of probes are

represented in each array

DNA

RNA

DNA microarrays applications

Expression arrays

SNPs arrays

CGH arrays

Promotor arrays

CpG arrays

Copy number

analysis

DNA regulation

Genotyping

Epigenetics

DNA methylation

AA

AB

BB

Data Mining/

Bioinformatics

Scanning

RNA

Isolation

Target

Labeling

Hybridization

Washing

Streptavidine-PE

Staining

Analysis

Ratio Image

Cy 5/Cy 3

Emission

Laser 1 Laser 2

Excitation

Reverse Transcription

IVT

(labeling with Cy3 and Cy5)

Cy3-labeled

cRNA

Cy5-labeled

cRNA

Two color array

Test-RNA Reference-RNA

PJares, Ultrastruct Pathol 2006

Gene Expression Profiling

Single color array

Reverse Transcription

IVT

Biotinilated cRNA

Fragmented cRNA

Signal

Present Call

Test-RNA

Reference-DNA Test-DNA

Mix &

co-hybridization CGH CGH-array

Fluorescent

detection

Balanced Gain Losses Balanced Gain Losses

Analysis

Genomic DNA

labeling

CGH-array

Resolution

5-10 Mb

Resolution

BAC-arrays:

Printing of 32.433 overlapping

BAC clones >100Kb

Agilent CGH array;

244k 60mer ;

8.9 kb median probe spacing

NimbleGen HD-arrays

Long oligos probes

2,100,000 (50mer-85mer)

1.1kb median probe spacing

Illumina human 1Mduo

1,200,000 loci per bead chip

1.5 kb median marker spacing

Affymetrix SNP array 6.0

1.800,000, intermarker distance

696bp

Eukaryotic cells

Formaldehyde

(protein-DNA cross-linking)

Cell lysis, sonication

Specific antibody

IP

Cross-link reversal

DNA purification

ChIP-on-chip

Labelling

DNA PCR Cy5 Labelling

DNA PCR Cy3 input Hybiridization to

Promotor microarrays

7.5 kb 2.45 kb Additional 2.5 kb for

1300 cancer genes 7 kb 3.2 kb

….TAGCCATCGGTANGTACTCAATGAT…. A

G

SNP

SNP Allele A= A

SNP Allele B= G

Allele-specific primer extension (ASPE)

Infinium Illumina SNP

ATCGGTAGCCATTCATGAGTTACTA

ATCGGTAGCCATCCATGAGTTACTA

Allele A

Allele B

Sequence-Specific Oligonucleotide

(SSO) Probes

Affymetrix Genotyping Array Design

AA AB BB Position: -4 -2 -1 0 +1 +3 +4

Sense

Antisense

genotype

SNP Arrays

A/A A/G G/G genotype

CG

GC Bisulfite

conversion

Allele-specific primer

annealling.

Single base extension

CpG Array: Infinium Methylation Assay

Human Methylation 27 k

Unmethylated DNA

Methylated DNA

Me

UG

GC

3’

5’

3’ Whole genome

amplification

Enzyme

fragmentation TG

CG 5’’

3’

Hybridization

N=12 samples

3’

GC GU

3’

Me 5’

CG CG 5’

GT 5’

GC 5’’ Stainned and

scanned

β

values

(0-1)

3’ 5’

Intensity [M]

Intensity [M] + [U]

3’

5’

5’

3’

3’

Pre-B

cell

Bone

Marrow

Pro-B

cell

Inmature

B-cell

IgM

Follicular area

IgM IgD

IgM IgD

** * * *

** * * *

** * * *

** * * *

** * * *

** * * *

** * * *

** * * *

** * * *

** * * *

** * * *

mature

naïve

B-cell

Plasmatic

cell

Memmory

cell

GC

B-Cell NHL Pathogenesis: Cellular origens, primary genetic alterations and target genes

B-LL CLL-B BL MALT-L

CLL-B

LPL

MCL FL DLBCL

MM

t(11;14)

CCND1

t(14;18)

BCL2

t(3q)

BCL6

t(8;14)

C-MYC

t(11;18)

API2-MLT

?

V(D)J

recombination

Somatic Hypermutation

Class switch recombination

centroblast/centrocytes

Ag

Diagnosis in Hematopathology From Morphology to an Integrated Diagnosis

Alizadeh et al. Nature 2000

CLL

FL

DLBCL

GC

Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling

Diffuse large B cell lymphoma (DLBCL) comprises at least two distinct diseases

Modified from Louis M. Staudt Annu. Rev. Med. 2002

Germinal Center

B-Cell

GC

Activated

B-cell

Rosenwald et al N Engl J Med 2001

N= 240

GC

n=100

vs

Burkitt Lymphoma

BL

Ki67

BL?

DLBCL?

To be or not to be …

Gene Expression Patterns in Burkitt Lymphoma

Step 1: Comparison for 21

MYC target genes as defined by MYC transfection

experiment in DLBCL

Step 2: Separate comparisons of BL with DLBCL-ABC, GCB

and primary mediastinal B-cell

lymphoma (PMBL)

Step 3: Construction of BL

predictor; also quantitative

predictor (0-100%)

Dave S et al N Engl J Med 2006

Molecular versus Pathology Diagnosis

Sandeep D et al N Engl J Med 2006

Gene expression profiles of the major classes of B-cell NHL

Aggressive lymphoma category can be further Subdivided into the different DLBCL subtypes

and Burkitt’s lymphoma

Breakpoints in

BCL-1 Region Chr 14

J H

Chr 11

MTC

TEL p94

CEN

CCND1

Mantle Cell Lymphoma t(11;14) Translocation and Cyclin D1

G1

G2

S

M

Growth Factors

CDK4

D1

Blastic

Classical

Cyclin D1 Negative MCL Variant

Cyclin D1

Cyclin D3 Cyclin D2 Fu K et al, Blood 2005

hematoxilin&

Eosin CCND1 SOX11

CCND1 SOX11 hematoxilin&

Eosin

Ana Mozos et al., haematologica 2009

SOX11 expression is highly specific for MCL and identifies Cyclin D1-negative subtype

MCL prognosis

Ki67

P<0.01

Tiemman et EMCL, Br J Haematol 2005; 131(1):29-38 Rosenwald A et al, Cancer Cell 2003, Feb;3(2):185-97

Proliferation

signature

Ruchlemer R et al, Br J Haematol 2004

2 years X

Conventional MCL

Indolent MCL

Study design

15 patients with conventional MCL (cMCL) that required chemotherapy at diagnosis

Generalized Polyadenopaty; ECOG>2 Evidence of disease progression at diagnosis Median follow-up 15 months, range 0.3-79

12 patients with indolent MCL (iMCL) not treated with chemotherapy and did not have evidence of clinical progression during > 2 years. Detection t(11;14) and overexpression CCND1 Initial diagnosis: SMZL (4), CLL (2), Leukemic Lymphoid neoplasm (NOS) (4), “in situ” MCL (2)

CD19

iMCL & cMCL clusterize together

Fernàndez V et al. Cancer Res 2010

cMCL & iMCL Chromosomal Alterations by SNP Arrays

Gain Loss

pUPD

cMCL iMCL

SNP 6.0

Gene Expression Profiling: conventional vs indolent MCL

Fernàndez V et al. Cancer Res 2010

Cyclin D1 Sox11

SOX11 expression in a independent validation series

Fernàndez V et al. Cancer Res 2010

Next Generation Sequencing

1953

DNA double helix

Watson Crick

Franklin

1975.

Frederick Sanger Sequencing method

1990.

The Human Genome Project start

1995.

Capillary electrophoresis Sequencer by Applied

1986.

First automated Sequencer by Applied

2003.

The Human Genome Project finish

Sequencing Tecnologies Evolution

Secuenciación Sanger 300 x106 $ > 10 años

Secuenciación Sanger 100 x106 $ 2-4 años

2004

2007

2008 Next-Generation 454 1 x106 2 meses

2008 Next-Gen Solexa 0.25 x106 2 meses

Jay Shendure and Hanlee Ji, Nature 2008

Sanger Sequencing NGS A

bout

2-3

weeks

2 d

ays

1 d

ay

5-7

days

Cluster generation Sequencing Sample Preparation

Library Generation

Target

enrichment*

1. DNA Inmobilization

Beads

Surface

Sequencing Chemistry (SBS)

- Ligation-Based sequencing

- Polymerase-Pyrosequencing

- Emulsion PCR

- Bridge Amplification

2. Amplification

- Polymerase-Reversible terminators

Single-end / Paired-end

Next-Generation Sequencing Technology

NGS Applications: Genomics & Transcriptomics

SNPs and CNVs

Chromosome

rearrangement

Genome

Sequencing

modified

Identification of the genetic alterations

present in 50 different cancer types

At least 500 patients for each tumor

Uncover traces of mutagenic influences

New targets for diagnosis and treatment

New therapies based on genomic

alterations identified in tumors

Proyecto Genoma

Leucemia Linfática Crónica

Chronic Lymphocytic Leukemia

• Most frequent leukemia in Western

countries (5-7 cases /100,000 /year)

• Heterogeneous disease with different

stages of progression and molecular

subtypes

• No effective therapy

• Pathogenesis

– Unknown initiating genetic alterations

– Microenvironment

– Evidence of genetic predisposition

• Geographic distribution

• Familiar clustering

• Susceptibility loci

• Environmental influences?

Years

Su

rviv

al

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1,0

4 8 12 16 20 24 28

Binet A

Binet B

Binet C

Months

0 100 200 300 400

0

50

100

Su

rviv

al

p = 0.001

Ig Mutations

Clinical Validation-1

Whole Gene Pooled Strategy 169 Patients

4 CLL

IGHV Unmutated

IGHV Mutated

Functional

Studies

WGS

Exome

Mutations

≥ 3% patients

Clinical Validation-2

194 Patients

Non-synonymous

Frameshifts Splicing sites

Expressed

Profile of Somatic Mutations in Four CLL Genomes

Solid lines: copy number; Bars: mutation density per 5 Mb

Dots: class 1 mutations (non-syn., frameshifts, splicing sites) Puente et al, Nature 2011

Genes recurrently mutated in CLL

Puente et al, Nature 2011

Gene Mutation

Mutated

cases / total

Overall

frequency (%)

Frequency in

IGHV-unmutated (%)

Frequency in

IGHV- mutated (%)

NOTCH1 P2515Rfs*4

Q2503*

F2482Ffs*2

29/255

1/255

1/255

12.2 20.4 7

MYD88 L265P 9/310 2.9 0.8 5.6

XPO1 E571K

E571G

3/165

1/165 2.4 4.6 0

KLHL6 F49L/L65P

L90F

L58P/T64A/Q81P

3/160 1.8 0 4.5

• CLL carries approximately 1 somatic mutations /MB (1000 per case)

• Identification of a potential mutational mechanism in IGHV hypermutated CLL

related to the activity of DNA polymerase eta

• Identification of 46 somatic mutations in coding regions with potential

functional effect. 5-20 per case

• Identification of 4 recurrent mutations with clinical implication

• NOTCH1 mutations are a frequent event in CLL – NOTCH1 mutations truncate and stabilize the protein and activate NOTCH1 pathway in CLL

– Predominant in IGHV unmutated CLL and associated with high risk factors (ZAP70/CD38)

• MYD88 mutations – Same mutation found in ABC DLBCL

– Activates NFkB pathway (IRAK1, STAT3)

– Promotes a high production of several chemokines (CCL2, CCL3, CCl4, IL6, ILR1A) in response to

TLR stimulation

WGS in CLL: Summary

Microarray genomic

selection array

Genomic DNA

NGS kit

Fragmented genome Target library

hybridization

SP coated magnetic beads

Microarray-based genomic selection Target enrichment in solution

Exome Sequencing: target enrichment

Profile of Somatic Mutations in 105 CLL Exomes

Quesada et al, Nature Genet 2012

Recurrent Mutated Genes in CLL

Quesada et al, Nature Genet 2012

Gene

Mutated

cases / total

Overall

frequency (%)

Frequency in

IGHV-unmutated (%)

Frequency in

IGHV- mutated (%)

NOTCH1 31/255 12.2 10.1 2.8

SF3B1 27/279 9.7 20.5 7.9

POT1 5/105 4.8 11.1 0

CHD2 5/105 4.8 0 8.3

LPP1D 5/105 4.8 5.0 5.0

• Exome sequencing of 105 CLL patients

• Identification of 1246 somatic mutations afectting about 1100 genes.

• Mutations in 78 genes are found in more than one patient.

• The initial functional analysis showed that the genes found mutated in

CLL significantly clustered in specific gene pathways including Toll-

like receptor pathway, RNA splicing and processing, among others.

• The different mutations are associated to different clinical groups.

• SF3B1 mutations are identified in patients with worst prognosis.

WGS in CLL: Summary

Lymphoma/Leukemia Molecular

Profiling Project University of Nebraska, Omaha

National Cancer Institute, Bethesda, MD

South-West Oncology Group

British Columbia Cancer Agency, Vancouver

University of Wurzburg, Wurzburg

Radium Hospital, Oslo

St Bartolomew Hospital, London

Hospital Clinic, University of Barcelona

Hematopathology Section

Pathology Department

Hospital Clinic,

University of Barcelona

E Campo

S Beà

M Pinyol

L Colomo

A Martinez

L Hernandez

V Amador

C Arroyo

A Navarro

P Jares

Consorcio ICGC - CLL

Hospital Clínico, Universidad de Barcelona Universidad de Oviedo, IUOPA Instituto de Investigaciones Biomédicas August Pi I Sunyer Centro de Regulación Genómica Instituto Catalán de Oncología Centro Investigación Cancer, Hospital Universitario (Salamanca) Centro Nacional Investigaciones Oncológicas Barcelona Supercomputer Center Universidad de Santiago de Compostela Universidad de Deusto Universidad Pompeu Fabra Hospital Clinico de Valencia Hospital General de Asturias Hospital Marques de Valde cilla Red de Investigación Cooperativa del Cáncer (RTICC) Redes Nacionales del Banco de DNA y de Tumores Instituto Nacional de Bioinformática (INB) Centro Nacional de Analisis Genómico

Ministerio de Ciencia e Innovación Instituto de Salud Carlos III

X

NTM

α-tub.

NOTCH1-unmutated NOTCH1-mutated Ju

rka

t

DTX3 HES1

NOTCH4 CTBP1

PSENEN DVL2 DTX4

NOTCH2 APH1A

NCSTN CREBBP

DVL3 NCOR2 PSEN1

JAG2 NOTCH1

JAG1 DTX1

ADAM17 MAML2

EP300 NUMB

NUMBL

NOTCH1- mutated NOTCH1-unmutated

Puente et al, Nature 2011

MYD88 oncogenic activation in CLL

NF-kB pathway

MAPK pathways

Inflammatory cytokines

and chemokines

IRAKs

MYD88

TLR

E52DEL E52DEL wt L265P wt wt wt L265P L265P

CCL2 CCL4 CCL3 IL6

IRAK1

MyD88

IRAK1

MyD88

IP:M

yD

88

un

bo

un

d

L265P WT

MYD88

L265P WT

p-IkBa

IkBa

p-p65

p65

b-actin wt mut

0

1

2

MYD88 status

NF

-B

p6

5 a

cti

va

tio

n

T>C (L265P)

MYD88 oncogenic activation in CLL may

promote a favorable microenvironment

NF-kB pathway

MAPK pathways

Inflammatory cytokines

and chemokines

IRAKs

MYD88

TLR

BCR

CCL2

CCL3

CCL4

Macrophages

Nurse Like-cells

T-cells

SYK

E52DEL E52DEL wt L265P wt wt wt L265P L265P

CCL2 CCL4 CCL3 IL6

Mutacions Somàtiques en la maquinària

molecular del processament del RNA en LLC

Pre-mRNA

Spliced-mRNA

SF3B1, U2AF2,

SFRS1, SFRS7,

XPO1, NXF1

EIF4A3,

MAGOH, NCBP2

RBMX,

SF3B1

SF3B1 Mutations in CLL

FOXP1 SF3B1

Tumor Mutated

Genes Frequency

Low grade gliomas

Glioblastoma

IDH1/IDH2

70%

12%

Ovary

• Granulosa Cell tumor

• Clear cell Ca

• Endometrioid Ca

FOXL2

ARID1A

99%

46%

30%

Clear Cell Renal Cancer

SETD2

JAR

UTX

PBRM1

15%

44%

Somatic Mutations in Exome/Transcriptome

Tumor (yr) Somatic

Mutations Non Synonymous Clinical Validation

AML (2008,2009,2010) 750 10-12 DNMT3A (22%)

IDH1 (16%)

Breast

Lobular Met (2009)

-

32

ERBB2 (1.5%)

HAUS (1%)

Basal-like (2009) - 50

Lung

Small-cell (cell line) (2009)

23,000

100

Not-performed

Non-small cell lung (2009) - 378

Melanoma (cell line) (2009)

33,000 187 Not-performed

Hepatocellular Ca HVC (2011) 11,000 70 Not-performed

Multiple Myeloma (2011)

20 cases

7,500 35 10

Different pathways

Somatic Mutations in WGS Studies

Genome alterations than can be detected by NGS

Meyerson M, et al. Nature Reviews 2010

NGS Applications: Genomics

Classic

MCL

Blastoid

MCL

Sox11+

Unmutated/Minimally

Mutated IG

“In situ” MCL

lesion

Naïve B-cell

Pre B-Cell

t(11;14)

Cyclin D1 Neg

Genomic Instability,

Proliferation, and cell survival

Hypermutated IG

SOX11-

Non-nodal, leukemic

and splenic MCL

Genetically stable (del)17p

Sox11-

SOX 11, a new MCL gene or just a biomarker?

?

SOX 11, a new MCL gene or just a biomarker?

N=132 samples

CpG methylation array

SOX11

SOX11 ChIP-on-chip

7 kb 3.2 kb

NimbleGen HD2

Z138 (Sox11+) JVM2 (Sox11-)

Cy5 Cy3

SOX11 Ab

Promotors bound by

SOX11

2.1 M Promoter array

GENE TITAN MULTI-CHANNEL INSTRUMENT

PEG arrays

16, 24, and 96

1. Presència d’unes 1000 mutacions somàtiques en el genoma de cada LLC

2. Identificació de 46 mutacions en les regions codificants del genoma, 5-20 per cas

3.Identificació de 4 mutacions recurrents amb implicacions clíniques

4.Desenvolupament d’un mètode bioinformàtic altament eficaç per detectar mutacions somàtiques